• Journal of the Society of Naval Architects of Korea
• /
• v.56 no.2
• /
• pp.143-151
• /
• 2019

This study describes a method for analyzing log data generated in a process using process mining techniques. A system for collecting and analyzing a large amount of log data generated in the process of manufacturing an offshore plant piping material was constructed. The analyzed data was visualized through various methods. Through the analysis of the process model, it was evaluated whether the process performance was correctly input. Through the pattern analysis of the log data, it is possible to check beforehand whether the problem process occurred. In addition, we analyzed the process performance data of partner companies and identified the load of their processes. These data can be used as reference data for pipe production allocation. Real-time decision-making is required to cope with the various variances that arise in offshore plant production. To do this, we have built a system that can analyze the log data of real - time system and make decisions.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.51-51
• /
• 2023

최근 기후의 급격한 변화 및 이상기후로 인해 전 세계적으로 가뭄의 발생빈도가 증가하고 있는 추세이다. 우리나라의 경우 지역·계절별 강수량의 편차로 인해 국지적으로 극심한 가뭄이 발생하고 있으며, 향후 피해는 더욱 증가할 것으로 예측하고 있다. 농업가뭄은 농작물 생육에 따른 수확량 및 수자원 이용에 직접적인 영향을 미치고 있으며, 농업수리시설물의 의존도가 높기 때문에 저수지의 대응능력과 농경지의 수리답 시설이 농업가뭄 대응을 위한 중요한 지표로써 활용되고 있다. 본 연구에서는 수리시설물의 가뭄대응능력과 평야부 농경지의 가뭄빈도를 이용하여 농업가뭄 취약성 평가를 수행하였다. 2015년 이후 매년 가뭄이 발생하는 충청남도 태안군을 시범지역으로 선정하였으며, 논 중심의 농업가뭄을 평가하기 위해 기상영향, 가뭄발생현황, 보조수원능력, 가뭄대응능력 4가지의 관련 항목을 선정하였다. 기상영향, 가뭄발생현황, 보조수원현황 항목은 계수화를 위해 데이터 속성 정보만을 이용하여 가중치를 산정하는 엔트로피 (Entropy) 방법을 적용하였으며, 가뭄대응능력 항목은 농업수리시설물과 농경지 평균 가뭄빈도 분석을 통해 점수화를 수행하였다. 본 연구의 결과는 지역별로 선제적인 가뭄대응 우선순위를 결정할 수 있고, 용수공급의 효율화 등 논 중심의 농업가뭄 대응을 위한 기초자료로써 활용될 수 있을 것으로 판단된다.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.19 no.3
• /
• pp.153-163
• /
• 2017

The objective of this study is to enhance the model's speed of estimating weather variables (e.g., minimum/maximum temperature, sunshine hour, PRISM (Parameter-elevation Regression on Independent Slopes Model) based precipitation), which are applied to the Agrometeorological Early Warning System (http://www.agmet.kr). The current process of weather estimation is operated on high-performance multi-core CPUs that have 8 physical cores and 16 logical threads. Nonetheless, the server is not even dedicated to the handling of a single county, indicating that very high overhead is involved in calculating the 10 counties of the Seomjin River Basin. In order to reduce such overhead, several cache and parallelization techniques were used to measure the performance and to check the applicability. Results are as follows: (1) for simple calculations such as Growing Degree Days accumulation, the time required for Input and Output (I/O) is significantly greater than that for calculation, suggesting the need of a technique which reduces disk I/O bottlenecks; (2) when there are many I/O, it is advantageous to distribute them on several servers. However, each server must have a cache for input data so that it does not compete for the same resource; and (3) GPU-based parallel processing method is most suitable for models such as PRISM with large computation loads.

• Proceedings of the KSR Conference
• /
• 2011.10a
• /
• pp.1020-1026
• /
• 2011

In this paper, we propose a method that measures the height and stagger of an catenary using the laser profile images. One line laser and area scanner CCD cameras are used. To quickly and accurately extract, from a photographed image, the area of the overhead line on which the line laser is shone, we consider the established fact that the catenary is the lowest among the electric wires. Here we are solving the the distance to the catenary if we know the distance the camera is from the ground and the angle of the catenary in the field of view. The angle will be related to the number of pixels in the image. This pixels per degree is a constant for the camera. Also, because of the different pixel resolution of the camera according to the overhead line position, we compensate the measurement result through camera calibration.

• Korean Chemical Engineering Research
• /
• v.58 no.4
• /
• pp.573-580
• /
• 2020

Hydrogen emerged as a sustainable transport energy source. To increase hydrogen utilization, hydrogen refueling stations must be available in many places. However, this requires large-scale financial investment. This paper proposed a methodology for selecting the optimal location to maximize the use of hydrogen charging stations. The location of gas stations and natural gas charging stations, which are competing energy sources, was first considered, and the expected charging demand of hydrogen cars was calculated by further reflecting data such as population, number of registered vehicles, etc. Using k-medoids clustering, one of the machine learning techniques, the optimal location of hydrogen charging stations to meet demand was calculated. The applicability of the proposed method was illustrated in a numerical case of Seoul. Data-based methods, such as this methodology, could contribute to constructing efficient hydrogen economic systems by increasing the speed of hydrogen distribution in the future.

• Journal of the Korean Institute of Telematics and Electronics D
• /
• v.36D no.1
• /
• pp.63-73
• /
• 1999

This paper presents new pipeline architecure for low power and high speed digital FIR filters. The proposed architecture based on retiming technique achieves enhancement on speed by sharing the input delay stage with multiplication of input data and on power combined with supply voltage scaling down technique. An 8-tap digital FIR filter for PRML disk-drive read channels adopting the proposed pipeline architecture has been designed and fabricated with 0.8${\mu}m$ CMOS double metal process technology. Measured results show that the designed FIR filter operates to 192 MHz in average and dissipates 1.22 mW/MHz at 3.3.V power supply. As a result, the proposed architecture improves speed by about 16% and reduces power dissipation by about 23% when operating at the same throughput.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.21 no.4
• /
• pp.149-160
• /
• 2011

Smart Grid is the next-generation intelligent power grid that maximizes energy efficiency with the convergence of IT technologies and the existing power grid. It enables consumers to check power rates in real time for active power consumption. It also enables suppliers to measure their expected power generation load, which stabilizes the operation of the power system. However, there are high possibility that various kinds of security threats such as data exposure, data theft, and privacy invasion may occur in interactive communication with intelligent devices. Therefore, to establish a secure environment for responding to such security threat with the smart grid, the key management technique, which is the core of the development of a security mechanism, is required. Using a hash chain, this paper suggests a group key management mechanism that is efficiently applicable to the smart grid environment with its hierarchical structure, and analyzes the security and efficiency of the suggested group key management mechanism.

• The Journal of Bigdata
• /
• v.5 no.2
• /
• pp.111-120
• /
• 2020

Despite the recent economic contraction caused by the Corona 19 incident, interest in the residential environment is growing as more people live at home due to the increase in telecommuting, thereby increasing demand for remodeling. In addition, the government's real estate policy is also expected to have a visible impact on the sales of the interior and furniture industries as it shifts from regulatory policy to the expansion of housing supply. Accurate demand forecasting is a problem directly related to inventory management, and a good demand forecast can reduce logistics and inventory costs due to overproduction by eliminating the need to have unnecessary inventory. However, it is a difficult problem to predict accurate demand because external factors such as constantly changing economic trends, market trends, and social issues must be taken into account. In this study, LSTM model and 1D-CNN model were compared and analyzed by artificial intelligence-based time series analysis method to produce reliable results for manufacturers producing furniture components.

• Membrane Journal
• /
• v.33 no.1
• /
• pp.34-45
• /
• 2023

Two computational intelligence techniques namely artificial neural networks (ANN) and support vector machine (SVM) are employed to model the permeate flux based on seven input variables including time, transmembrane pressure, rotating velocity, the pore diameter of the membrane, dynamic viscosity, concentration and density of the feed fluid. The best-fit model was selected through the trial-error method and the two statistical parameters including the coefficient of determination (R²) and the average absolute relative deviation (AARD) between the experimental and predicted data. The obtained results reveal that the optimized ANN model can predict the permeate flux with R² = 0.999 and AARD% = 2.245 versus the SVM model with R² = 0.996 and AARD% = 4.09. Thus, the ANN model is found to predict the permeate flux with high accuracy in comparison to the SVM approach.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.23 no.12
• /
• pp.201-209
• /
• 2009

In power plant operations, sensor values often exhibit erroneous values due to their failures or the intrusions of various noises. However, most of the power plant monitoring and fault diagnosis systems perform their tasks based on the assumptions that the collected sensor values are correct all the times. These assumptions, which are not valid, often lead to serious consequences such as power plant trips. In this paper, we propose a power plant sensor value validation technique that can utilize the relationships existing among the sensor values as the sensor redundancy. The proposed technique is applied to the flow meters installed along boiler feed water systems of a typical tubular type boiler thermal power plant and shows a good potential of future applications.